Diagnostics of the Topic Model for a Collection of Text Messages Based on Hierarchical Clustering of Terms.

The problem of constructing a correct topic model is relevant for the automatic processing of large collections of text messages tasks. This paper considers an approach to the topic categorization assessing for a collection of short text messages (labeled up by experts) based on the clustering of terms that make up the message text. The results of a computer experiment on clustering a set of terms are presented and discussed. As part of the experiment, a graph was constructed that reflects the relations and some numerical characteristics of the terms that form the topic model for a collection of messages. Analysis of the structure of the graph allows one to generate some practical recommendations for reorganizing the topic model presented in the expert labeled text collection. [ABSTRACT FROM AUTHOR]